Finally, we can define quantitative measures that try to indicate the quality of an explanation by measuring the behaviour of the model or explanation after applying specific perturbations [1]}, [2]}. A simple example of this kind of measure is Deletion [3]}. Here, we iteratively mask the top \(n\)  most important features, as indicated by the explanation. If the features that were marked as important are truly important, we would expect the output of the model to drop rapidly with increasing \(n\) .
